Recently, event-centered commonsense knowledge has attracted much attention [1]}, [2]}, [3]}, [4]}, because of understanding events is an important component of NLP. Given a daily-life event, human can easily understand it and reason about its causes, effects, and so on. However, it still remains a challenging task for NLP
systems. This is partly due to most of them are trained for
task-specific datasets or objectives, which results in models
that are adapt at finding task-specific underlying correlation
patterns but have limited capability in simple and explainable
commonsense reasoning [5]}.
